Triple

T25856081
Position Surface form Disambiguated ID Type / Status
Subject New York City Transit rail yard network E651346 entity
Predicate hasPart P35 FINISHED
Object 36th–38th Street Yard
The 36th–38th Street Yard is a New York City Subway maintenance and storage facility in Brooklyn that services and stores trains for nearby lines.
 E1699480 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 36th–38th Street Yard | Statement: [New York City Transit rail yard network, hasPart, 36th–38th Street Yard]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: 36th–38th Street Yard
Triple: [New York City Transit rail yard network, hasPart, 36th–38th Street Yard]
Generated description
The 36th–38th Street Yard is a New York City Subway maintenance and storage facility in Brooklyn that services and stores trains for nearby lines.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e7ab39035c8190be15c8aaee1bb858 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f60267e08481908cd8cdcdcc4afa00 completed May 2, 2026, 1:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecb01ed081909965f317a2c082bb completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10edac42ec8190ac894ee9bd658b22 completed May 22, 2026, 11:58 p.m.
NED2 Entity disambiguation (via description) batch_6a10ee53bee48190bc7ab1f9a73c60da completed May 23, 2026, 12:01 a.m.
Created at: April 22, 2026, 8 a.m.